一元线性模型异方差的局部多项式回归  

Local Polynomial Regression for Heteroscedaticity in the Simple Linear Model

作　　者：何其祥[1] 郑明[2] 

机构地区：[1]上海财经大学应用数学系,上海200433 [2]复旦大学统计学系,200433

出　　处：《系统工程理论方法应用》2003年第2期153-156,共4页Systems Engineering Theory·Methodology·Applications

摘　　要：本文将局部多项式回归的非参数方法用于线性模型中异方差的估计 ,改进了传统的两阶段法 ,得到了估计的一致性和渐近正态性 ,为探讨估计的有限样本性 ,给出了若干模拟的例子。We introduce the extension of the nonparametric regression technique of local polynomial fitting with a kernel weight to heteroscedastic linear regression model. One noteworthy feature of our approach is avoiding the testing for heteroscedasticity. We establish the uniform consistency and derive the asymptotic distribution. Simulation results show that our approach is effective in finite sample situations as well.

关 键 词：一元线性模型 异方差性 局部多项式回归 线性回归模型 

分 类 号：O212.1[理学—概率论与数理统计]